The DOI matches its Crossref record; 41 of the 45 references it cites were found in a registry or an index.
Stacked Cross Attention for Image-Text Matching
Open accessOverview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Adding images to such measures (e.g., Vilbertscore [72], TIGEr [65], SCAN [75]) or using reference-free measures (e.g., CLIPScore [59]) can help, but degraded images can be a confound in their scores.”
From "It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models (2026) · cites this paper as [75]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
Bidirectional recurrent neural networks
Schuster, M., & Paliwal, K. K. (1997) · IEEE Transactions on Signal Processing · doi:10.1109/78.650093 · Cited by 10,172
Effective Approaches to Attention-based Neural Machine Translation
Luong, T., Pham, H., & Manning, C. D. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d15-1166 · Cited by 8,382
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv · doi:10.48550/arxiv.1502.03044 · Cited by 8,248
Research works printed but not linked: 6
- Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization. arXiv preprint arXiv:1607.06450 (2016) · arXiv
- Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: ICLR (2015)
- Chorowski, J.K., Bahdanau, D., Serdyuk, D., Cho, K., Bengio, Y.: Attention-based models for speech recognition. In: NIPS (2015)
- Faghri, F., Fleet, D.J., Kiros, J.R., Fidler, S.: VSE++: improved visual-semantic embeddings. arXiv preprint arXiv:1707.05612 (2017) · arXiv
- Peng, Y., Qi, J., Yuan, Y.: CM-GANs: cross-modal generative adversarial networks for common representation learning. arXiv preprint arXiv:1710.05106 (2017) · arXiv
- Zheng, Z., Zheng, L., Garrett, M., Yang, Y., Shen, Y.D.: Dual-path convolutional image-text embedding. arXiv preprint arXiv:1711.05535 (2017) · arXiv
Cited by
Sorted by citations
Items 401–500 of 1,001
Commonsense-Guided Semantic and Relational Consistencies for Image-Text Retrieval
Li, W., Yang, S. S., Li, Q., Li, X., & Liu, A.-A. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3289753 · Cited by 23
Cross-modal Consistency Learning with Fine-grained Fusion Network for Multimodal Fake News Detection
Li, J., Bin, Y., Zou, J., Wei, J., Wang, G., & Yang, Y. (2023) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3595916.3626397 · Cited by 23
Rich Features Embedding for Cross-Modal Retrieval: A Simple Baseline
Fu, X., Zhao, Y., Wei, Y., Zhao, Y., & Wei, S. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2957948 · Cited by 23
3SHNet: Boosting image–sentence retrieval via visual semantic–spatial self-highlighting
Ge, X., Xu, S., Chen, F., Wang, J., Wang, G., An, S., & Jose, J. M. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103716 · Cited by 22
Visual Global-Salient-Guided Network for Remote Sensing Image-Text Retrieval
He, Y., Xu, X., Chen, H., Li, J., & Pu, F. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3466389 · Cited by 22
Composed Image Retrieval via Explicit Erasure and Replenishment With Semantic Alignment
Zhang, G., Wei, S., Pang, H., Qiu, S., & Zhao, Y. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3204213 · Cited by 22
A Precise Framework for Rice Leaf Disease Image–Text Retrieval Using FHTW-Net
Zhou, H., Hu, Y., Liu, S., Zhou, G., Xu, J., Chen, A., Wang, Y., Li, L., & Hu, Y. (2024) · Plant Phenomics · doi:10.34133/plantphenomics.0168 · Cited by 22
Interclass-Relativity-Adaptive Metric Learning for Cross-Modal Matching and Beyond
Chen, F., Shao, J., Zhang, Y., Xu, X., & Shen, H. T. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3019710 · Cited by 22
Detector-Free Weakly Supervised Grounding by Separation
Arbelle, A., Doveh, S., Alfassy, A., Shtok, J., Lev, G., Schwartz, E., Kuehne, H., Levi, H., Sattigeri, P., Panda, R., et al. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00182 · Cited by 25
Iterative graph attention memory network for cross-modal retrieval
Dong, X., Zhang, H., Dong, X. M., & Lu, X. C. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107138 · Cited by 22
Fine-grained Semantics-aware Representation Learning for Text-based Person Retrieval
Wang, D., Yan, F., Wang, Y., Zhao, L., Xiao, L., Zhong, H., & Zhang, R. (2024) · International Conference on Multimedia Retrieval · doi:10.1145/3652583.3658054 · Cited by 25
Thread the Needle: Cues-Driven Multiassociation for Remote Sensing Cross-Modal Retrieval
Chen, Y., Huang, J., Sun, Z., Xiong, S., & Lu, X. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3509639 · Cited by 21
Cross-Modal Hashing via Diverse Instances Matching
Tu, J., Liu, X., Huang, Z., Hao, Y., Hong, R., & Wang, M. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3561659 · Cited by 23
Cross-lingual Cross-modal Pretraining for Multimodal Retrieval
Fei, H., Yu, T., & Li, P. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.285 · Cited by 26
Distributed Attention for Grounded Image Captioning
Chen, N., Pan, X., Chen, R., Yang, L., Lin, Z., Ren, Y., Yuan, H., Guo, X., Huang, F., & Wang, W. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475354 · Cited by 21
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching
Biten, A. F., Mafla, A., Gómez, L., & Karatzas, D. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00254 · Cited by 21
Wu, X., Mao, J., Xie, H., & Li, G. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.102977 · Cited by 21
Cross-modal Contrastive Learning for Generalizable and Efficient Image-text Retrieval
Lu, H., Huo, Y., Ding, M., Fei, N., & Lu, Z. (2023) · Machine Intelligence Research · doi:10.1007/s11633-022-1386-4 · Cited by 21
Learning From Noisy Correspondence With Tri-Partition for Cross-Modal Matching
Feng, Z., Zeng, Z., Guo, C., Li, Z., & Hu, L. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3318002 · Cited by 22
Zheng, F., Wang, X., Wang, L., Zhang, X., Zhu, H., Wang, L., & Zhang, H. (2023) · Sensors · doi:10.3390/s23208437 · Cited by 24
Multi-task Hierarchical Heterogeneous Fusion Framework for multimodal summarization
Zhang, L., Zhang, X., Han, L., Yu, Z., Liu, Y., & Li, Z. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103693 · Cited by 21
Evaluating Text-to-Image Matching using Binary Image Selection (BISON)
Hu, H., Misra, I., & van der Maaten, L. J. P. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00237 · Cited by 23
Self-citationPramanick, S., Akhtar, M. S., & Chakraborty, T. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v15i1.18080 · Cited by 21
Learning and Integrating Multi-Level Matching Features for Image-Text Retrieval
Lan, H., & Zhang, P. (2021) · IEEE Signal Processing Letters · doi:10.1109/lsp.2021.3135825 · Cited by 21
Strong and Weak Prompt Engineering for Remote Sensing Image-Text Cross-Modal Retrieval
Sun, T., Zheng, C., Li, X., Gao, Y., Nie, J., Huang, L., & Wei, Z. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3534474 · Cited by 24
Exploiting Natural Language for Efficient Risk-Aware Multi-Robot SaR Planning
Shree, V., Asfora, B., Zheng, R., Hong, S., Banfi, J., & Campbell, M. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3062798 · Cited by 20
Topic Scene Graph Generation by Attention Distillation from Caption
Wang, W., Wang, R., & Chen, X. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01560 · Cited by 20
Self-citationBilateral Temporal Re-Aggregation for Weakly-Supervised Video Object Segmentation
Lin, F., Xie, H., Liu, C., & Zhang, Y. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3127562 · Cited by 20
Coarse-to-fine dual-level attention for video-text cross modal retrieval
Jin, M., Zhang, H., Zhu, L., Sun, J., & Liu, L. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108354 · Cited by 20
Decoupled Cross-Modal Phrase-Attention Network for Image-Sentence Matching
Shi, Z., Zhang, T., Wei, X., Wu, F. H., & Zhang, Y. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3197972 · Cited by 20
Chen, C., Wang, D., Song, B., & Tan, H. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3243665 · Cited by 20
Rare-aware attention network for image–text matching
Wang, Y., Su, Y., Li, W., Sun, Z., Wei, Z., Nie, J., Li, X., & Liu, A.-A. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103280 · Cited by 20
Liu, H., Liu, S., An, R., Zhuo, Y., & Tao, J. (2023) · Mathematics · doi:10.3390/math11102279 · Cited by 20
Reservoir Computing Transformer for Image-Text Retrieval
Li, W., Ma, Z., Deng, L.-J., Wang, P., Shi, J., & Xiaopeng Fan, B. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611758 · Cited by 21
VLN-PETL: Parameter-Efficient Transfer Learning for Vision-and-Language Navigation
Qiao, Y., Zheng, Y. H., & Wu, Q. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01416 · Cited by 27
Improving Text-Based Person Retrieval by Excavating All-Round Information Beyond Color
Zhu, A., Wang, Z., Xue, J., Wan, X., Jin, J., Wang, T., & Snoussi, H. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3368217 · Cited by 20
Text-Guided Knowledge Transfer for Remote Sensing Image-Text Retrieval
Liu, A.-A., Yang, B., Li, W., Song, D., Sun, Z., Ren, T., & Wei, Z. (2024) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2024.3374381 · Cited by 20
Multimodal Social Media Fake News Detection Based on Similarity Inference and Adversarial Networks
Shan, F., Sun, H., & Wang, M. (2024) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2024.046202 · Cited by 22
Robust Noisy Correspondence Learning with Equivariant Similarity Consistency
Yang, Y., Wang, L., Yang, E., & Deng, C. D. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01676 · Cited by 21
Sun, Z., Zhao, M., Liu, G., & Kaup, A. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3489224 · Cited by 20
Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained Ship Classification
Lan, L., Wang, F., Zheng, X., Wang, Z., & Liu, X. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3509721 · Cited by 20
Multi-Head Attention with Diversity for Learning Grounded Multilingual Multimodal Representations
Huang, P.-Y., Chang, X., & Hauptmann, A. G. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1154 · Cited by 22
Self-attention guided representation learning for image-text matching
Qi, X., Zhang, Y., Qi, J., & Lu, H. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.03.129 · Cited by 20
Learning Relation Alignment for Calibrated Cross-modal Retrieval
Ren, S., Lin, J., Zhao, G., Men, R., An, Y., Zhou, J., Sun, X., & Yang, H. (2021) · doi:10.18653/v1/2021.acl-long.43 · Cited by 20
Masked Vision-language Transformer in Fashion
Ji, G.-P., Zhuge, M., Gao, D., Fan, D.-P., Sakaridis, C., & Gool, L. V. (2023) · Machine Intelligence Research · doi:10.1007/s11633-022-1394-4 · Cited by 20
EAML: ensemble self-attention-based mutual learning network for document image classification
Bakkali, S., Ming, Z., Coustaty, M., & Rusiñol, M. (2021) · International Journal on Document Analysis and Recognition (IJDAR) · doi:10.1007/s10032-021-00378-0 · Cited by 20
Dig into Multi-modal Cues for Video Retrieval with Hierarchical Alignment
Wang, W., Zhang, M., Chen, R., Cai, G., Zhou, P., Peng, P., Guo, X., Wu, J., & Sun, X. (2021) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/154 · Cited by 19
Learning Aligned Image-Text Representations Using Graph Attentive Relational Network
Jing, Y., Wang, W., Wang, L., & Tan, T. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3048627 · Cited by 19
Title-and-Tag Contrastive Vision-and-Language Transformer for Social Media Popularity Prediction
Chen, W., Huang, C., Yuan, W., Chen, X., Hu, W., Zhang, X., & Zhang, Y. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3551568 · Cited by 19
Self-citationGong, Y., & Cosma, G. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.109272 · Cited by 19
Qin, X., Li, L., Hao, F., Ge, M., & Pang, G. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103575 · Cited by 19
Negative Pre-aware for Noisy Cross-Modal Matching
Zhang, X., Li, H., & Ye, M. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i7.28564 · Cited by 23
Selectively Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching
Li, Z., Guo, C., Wang, X., Feng, Z., & Du, Z. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3480949 · Cited by 19
Huang, P.-Y., Vaibhav, Chang, X., & Hauptmann, A. G. (2019) · International Conference on Multimedia Retrieval · doi:10.1145/3323873.3325043 · Cited by 19
Real-world Cross-modal Retrieval via Sequential Learning
Song, G., & Tan, X. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3002177 · Cited by 19
YORO - Lightweight End to End Visual Grounding
Ho, C.-H., Appalaraju, S., Jasani, B. A., Manmatha, R., & Vasconcelos, N. M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25085-9_1 · Cited by 19
Modeling Thousands of Human Annotators for Generalizable Text-to-Image Person Re-identification
Jiang, J., Ding, C., Tan, W., Wang, J., Jin, T., & Xu, X. (2025) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52734.2025.00861 · Cited by 18
Visual Relations Augmented Cross-modal Retrieval
Guo, Y., Chen, J., Zhang, H., & Jiang, Y. (2020) · International Conference on Multimedia Retrieval · doi:10.1145/3372278.3390709 · Cited by 18
Pang, H., Wei, S., Zhang, G., Zhang, S., Qiu, S., & Zhao, Y. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3208742 · Cited by 18
An effective spatial relational reasoning networks for visual question answering
Shen, X., Han, D., Chen, C., Luo, G., & Wu, Z. (2022) · PLoS ONE · doi:10.1371/journal.pone.0277693 · Cited by 18
Contrasting Dual Transformer Architectures for Multi-Modal Remote Sensing Image Retrieval
Rahhal, M. M. A., Bencherif, M. A., Bazi, Y., Alharbi, A., & Mekhalfi, M. L. (2022) · Applied Sciences · doi:10.3390/app13010282 · Cited by 20
Li, S., Xu, X., Jiang, X., Shen, F., Sun, Z., & Cichocki, A. S. (2024) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3639469 · Cited by 18
LIMITR: Leveraging Local Information for Medical Image-Text Representation
Dawidowicz, G., Hirsch, E., & Tal, A. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01935 · Cited by 18
Cross-modal semantic aligning and neighbor-aware completing for robust text–image person retrieval
Gong, T., Wang, J., & Zhang, L. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102544 · Cited by 18
Cheng, Q., & Gu, X. (2020) · Digital Signal Processing · doi:10.1016/j.dsp.2020.102866 · Cited by 18
Revisiting Image-Language Networks for Open-Ended Phrase Detection
Plummer, B. A., Shih, K. J., Li, Y., Xu, K., Lazebnik, S., Sclaroff, S., & Saenko, K. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3029008 · Cited by 18
Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query
Cai, G., Zhang, J., Jiang, X., Gong, Y., He, L., Yu, F., Peng, P., Guo, X., Huang, F., & Sun, X. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00185 · Cited by 18
Wang, X., Li, L., Li, Z., Wang, X., Zhu, X., Wang, C., Huang, J., & Xiao, Y. (2023) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3539597.3570481 · Cited by 18
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language QueriesPreprint
Tan, F., Cascante-Bonilla, P., Guo, X., Wu, H., Feng, S., & Ordóñez, V. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.03826 · Cited by 18
Dividing and Conquering Cross-Modal Recipe Retrieval: from Nearest Neighbours Baselines to SoTAPreprint
Fain, M., Twomey, N., Ponikar, A., Fox, R., & Bollegala, D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.12763 · Cited by 19
Focus your attention: A focal attention for multimodal learning
Liu, C., Mao, Z., Zhang, T., Liu, A.-A., Wang, B., & Zhang, Y. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3046855 · Cited by 17
Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation
Wu, J.-J., Chang, A. C.-H., Chuang, C.-Y., Chen, C.-P., Liu, Y.-L., Chen, M.-H., Hu, H.-N., Chuang, Y., & Lin, Y. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02530 · Cited by 24
Self-citationDomain knowledge-driven image captioning for bridge damage description generation
Chai, C., Gao, Y., Xiong, G., Liu, J., & Li, H. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106116 · Cited by 17
BCAN: Bidirectional Correct Attention Network for Cross-Modal Retrieval
Liu, Y., Liu, H., Wang, H., Meng, F., & Liu, M. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3276796 · Cited by 18
Qiu, J., Han, W., Zhu, J., Xu, M., Rosenberg, M., Liu, E., Weber, D. J., & Zhao, D. X. (2023) · Findings of the Association for Computational Linguistics: EACL · doi:10.18653/v1/2023.findings-eacl.33 · Cited by 21
Deep visual-linguistic fusion network considering cross-modal inconsistency for rumor detection
Yang, Y., Bao, R., Guo, W., Zhan, D., Yin, Y., & Yang, J. J. (2023) · Science China Information Sciences · doi:10.1007/s11432-021-3530-7 · Cited by 19
Learning emotional prompt features with multiple views for visual emotion analysis
Xu, Q., Wei, Y., Yuan, S., Wu, J., Wang, L., & Wu, C. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102366 · Cited by 19
Layerwised multimodal knowledge distillation for vision-language pretrained model
Wang, J., Liao, D., Zhang, Y., Xu, D., & Zhang, X. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106272 · Cited by 17
REO-Relevance, Extraness, Omission: A Fine-grained Evaluation for Image Captioning
Jiang, M., Hu, J., Huang, Q., Zhang, L., Diesner, J., & Gao, J. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1156 · Cited by 17
Multi-Modal Memory Enhancement Attention Network for Image-Text Matching
Ji, Z., Lin, Z., Wang, H., & He, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2975594 · Cited by 17
Re-ranking image-text matching by adaptive metric fusion
Niu, K., Huang, Y., & Wang, L. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107351 · Cited by 17
Hierarchical and complementary experts transformer with momentum invariance for image-text retrieval
Zhang, Y., Ji, Z., Pang, Y., & Han, J. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112912 · Cited by 16
Scalable Multi-grained Cross-modal Similarity Query with Interpretability
Zhu, M., Shen, D., Lixin, X., & Wang, X. (2021) · Data Science and Engineering · doi:10.1007/s41019-021-00162-4 · Cited by 16
Latent Space Semantic Supervision Based on Knowledge Distillation for Cross-Modal Retrieval
Zhang, L., & Wu, X. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3220051 · Cited by 16
Bose, P., Rana, P., & Ghosh, P. (2023) · IEEE Access · doi:10.1109/access.2023.3299877 · Cited by 18
Integrating listwise ranking into pairwise-based image-text retrieval
Li, Z., Guo, C., Wang, X., Zhang, H., & Wang, Y. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111431 · Cited by 16
Multimodal Composition Example Mining for Composed Query Image Retrieval
Zhang, G., Li, S., Wei, S., Ge, S., Cai, N., & Zhao, Y. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3359062 · Cited by 17
Hierarchical matching and reasoning for multi-query image retrieval
Ji, Z., Li, Z., Zhang, Y., Wang, H., Pang, Y., & Li, X. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106200 · Cited by 16
An Overview of Text-Based Person Search: Recent Advances and Future Directions
Niu, K., Liu, Y., Long, Y., Huang, Y., Wang, L., & Zhang, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3376373 · Cited by 18
Reference-Aware Adaptive Network for Image-Text Matching
Xiong, G., Meng, M., Zhang, T., Zhang, D., & Zhang, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3392619 · Cited by 16
Breaking Through the Noisy Correspondence: A Robust Model for Image-Text Matching
Shi, H., Liu, M., Mu, X., Song, X., Hu, Y., & Nie, L. (2024) · ACM Transactions on Information Systems · doi:10.1145/3662732 · Cited by 18
Knowledge Graph Enhanced Multimodal Transformer for Image-Text Retrieval
Zheng, J., Liang, M., Yu, Y., Li, Y., & Xue, Z. (2024) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde60146.2024.00013 · Cited by 19
GADNet: Improving image–text matching via graph-based aggregation and disentanglement
Pu, X., Wang, Z., Yuan, L., Wu, Y. C., Jing, L., & Gao, X. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110900 · Cited by 16
Remote Sensing Image-Text Retrieval With Implicit-Explicit Relation Reasoning
Yang, L., Zhou, T., Ma, W., Du, M., Liu, L., Li, F., Zhao, S., & Wang, Y. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3466909 · Cited by 17
Multi-view visual semantic embedding for cross-modal image–text retrieval
Li, Z., Guo, C., Wang, X., Zhang, H., & Hu, L. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111088 · Cited by 16
Cross-modal independent matching network for image-text retrieval
Ke, X., Chen, B., Yang, X., Cai, Y., Líu, H., & Guo, W. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111096 · Cited by 16
A Strong and Robust Baseline for Text-Image Matching
Liu, F., & Ye, R. (2019) · Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW) · doi:10.18653/v1/p19-2023 · Cited by 17
Cross-modal recipe retrieval via parallel- and cross-attention networks learning
Cao, D., Chu, J., Zhu, N., & Nie, L. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.105428 · Cited by 16
Stacked squeeze-and-excitation recurrent residual network for visual-semantic matching
Wang, H., Ji, Z., Lin, Z., Pang, Y., & Li, X. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107359 · Cited by 16
Hierarchical Visual-Textual Knowledge Distillation for Life-Long Correlation Learning
Peng, Y., Qi, J., Ye, Z., & Zhuo, Y. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01392-1 · Cited by 16
Metadata
- Authors
- Lee, K.-H., Chen, X., Hua, G., Hu, H., & He, X.
- Affiliations
- Microsoft (United States) (US)
- Jingdong (China) (CN)
- Corresponding author
- Lee, Kuang-Huei
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 212-228
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2962964995
- Cited by
- 1,402
- References
- 45
- Citations by year
- 2026: 104 · 2025: 202 · 2024: 244 · 2023: 241 · 2022: 201 · 2021: 211 · 2020: 131 · 2019: 63 · 2018: 5
- FWCI
- 30.89
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- image-text matching, cross-attention, vision-language alignment, image retrieval, text retrieval, interpretability, MS COCO, Flickr30k
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review